code: def _set_ax_settings(ax):
      ax.plot([0, 1], [0, 1], "k--")
      ax.set_xlim([0.0, 1.0])
      ax.set_ylim([0.0, 1.05])
      ax.set_xlabel("False Positive Rate")
      ax.set_ylabel("True Positive Rate")
      ax.set_title("ROC")
      ax.legend(loc="best")
  
imports: import numpy
  import matplotlib.pyplot
  from sklearn.metrics import roc_curve, auc
  from sklearn.preprocessing import label_binarize
  from ..telemetry import SKLearnEvaluationLogger
  from ..util import is_column_vector, is_row_vector
  from sklearn_evaluation import __version__
  import json
  from pathlib import Path
  from sklearn_evaluation.plot.plot import AbstractPlot, AbstractComposedPlot
  from ploomber_core.exceptions import modify_exceptions
label_desc: Use image node_id 2 for calling a global function with example usage: _set_ax_settings(ax) without return types